wayground logo

Free Printable Worksheets

Font size

S
M
L
XL
Worksheets

CS F415 Data Mining - Clustering Inclass Assignment

Total questions: 10

Worksheet time: 10mins

Name
Class
Date
1.

Silhouette Coefficient is defined as follows:

S(i) = ( b(i) – a(i) ) / ( max { ( a(i), b(i) ) }

a)

a(i) is the average dissimilarity of ith object to all other objects in the same cluster.

b)

b(i) is the average dissimilarity of ith object with all objects in the closest cluster.

c)

a(i) is the average similarity of ith object to all other objects in the same cluster.

d)

b(i) is the average dissimilarity of ith object with all objects in the same cluster.

2.

Putting a heterogeneous object into a pure cluster should be penalized less than putting it into a rag bag. True or False

a)

True

b)

False

3.

Which of the following linkage measures is most robust to noise?

a)

Min Average

b)

Max Average

c)

Group Average

4.

Which of the following linkage measures lead to compact clusters?

a)

Min

b)

Max

c)

Group Average

5.

A border point is a point that has ___________ than MinPts within ε, but lies within the ε radius of a core point.

a)

fewer neighbours

b)

more neighbours

c)

equal number of neighbours

d)

None of the above

6.

Which of the following algorithm is suitable to cluster nominal data?

a)

K-Means

b)

CLARA

c)

K-Medoids

d)

K-Modes

7.

Suppose in a village of 100 people, 30 people got infested with a rare virus, which starts showing visible signs in a month. You are a clinician and you decided to use a detector to identify infested people before it’s too late . Your device detected that 40 out of 100 people were infested with virus (Detected Positive). Your findings now mapped with actual cases are shown in the figure. Can you find the precision of your detector:

a)

66.67

b)

50

c)

33.3

d)

25

8.

Can you find the recall of the detector?

a)

66.67

b)

25

c)

50

d)

33.33

9.

Which of the following can act as possible termination conditions in K-Means?

1. For a fixed number of iterations.

2. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum.

3. Centroids do not change between successive iterations.

4. Terminate when RSS falls below a threshold.

a)

1, 3 and 4

b)

1, 2 and 3

c)

1, 2 and 4

d)

All of the above

10.

Assume, you want to cluster 7 observations into 3 clusters using K-Means clustering algorithm. After first iteration clusters, C1, C2, C3 has following observations:

C1: {(2,2), (4,4), (6,6)}

C2: {(0,4), (4,0)}

C3: {(5,5), (9,9)}

What will be the cluster centroids if you want to proceed for second iteration?

a)

C1: (4,4), C2: (2,2), C3: (7,7)

b)

C1: (6,6), C2: (4,4), C3: (9,9)

c)

C1: (2,2), C2: (0,0), C3: (5,5)

d)

None of these